Protótipo para análise técnico-econômica de bombas funcionando como turbinas em redes de distribuição de água

Abstract

The growing need for sustainable solutions in water distribution networks requires technologies that optimize energy efficiency and reduce operating costs. However, choosing the best alternative for implementing Pumps Operating as Turbines (BFTs) is challenging due to the multiple technical and economic criteria involved. Therefore, this study proposes a decision support model, employing multicriteria techniques and computer programming to assist in selecting the most viable alternative within different scenarios. The analysis focuses on the technical-economic feasibility of BFTs in Water Distribution Networks (RDAs), using the TOPSIS method, where data will be evaluated and classified by similarity to ideal conditions. Implemented in Python, the system ensures calculation accuracy, with a graphical interface called FliessEnergy, hosted by Vercel, with a responsive and scalable layout, providing an optimized user experience. Practical application with real RDA data demonstrated its effectiveness in prioritizing the most advantageous alternatives. The results indicated that Scenario 1 presented the best configuration for implementing BFTs, while Scenario 5 was the least favorable alternative. This classification of alternatives helps managers make decisions, taking into account both the proximity to the best conditions and the distance from the worst. To assess the reliability and consistency of the codes, PyTOPS, free software that allows several simulations with changes in the weights of the criteria, was used. A total of 500 simulations were performed, resulting in reduced variability between the scenarios, which reinforces the robustness of the model and its ability to generate consistent classifications even with small changes in the parameters. The model proved consistent and reliable, offering a useful instrument for evaluating the implementation of BFTs in RDAs. It is expected that, with future improvements and integration of databases, this solution can contribute significantly to strategic decisions in the sanitation sector in Brazil.